Open Position for Post-Doctoral Researcher on Artificial intelligence (AI)-based grain boundary[...]

Organisation/Company: GT-CNRS IRL-2958

Department: Mechanical Engineering

Research Field: Engineering » Materials engineering

Researcher Profile: First Stage Researcher (R1)

Positions: Postdoc Positions

Country: France

Application Deadline: 20 Apr 2025 - 22:00 (Europe/Vienna)

Type of Contract: Temporary

Job Status: Full-time

Hours Per Week: 35

Is the job funded through the EU Research Framework Programme? Not funded by a EU programme

Is the Job related to staff position within a Research Infrastructure? Yes

Offer Description

The structure of the grain boundary has been known to play a critical role in many materials properties such as intergranular cracking, corrosion resistance and plastic flow (dislocation pile ups, slip transmission, etc.). To make use of the relationship between grain boundary structure and the properties of materials, the field of grain boundary engineering has been steadily developed since its introduction by Watanabe. The key idea of this concept is to optimize the properties of a material by controlling and designing the grain boundary network of a polycrystal.

To this aim, it is necessary to associate the structure of a grain boundary with positive or negative consequences for a given application. Unfortunately, establishing the relationship between the structure and the resulting properties is not an easy task because grain boundaries have extremely complex features, whose properties depend on all the parameters needed for their mathematical description (5 DOF). Recently, data analytical methods have been proposed to better associate grain boundaries with materials properties. Nevertheless, a linkage of the atomic structure considering the atomic structure of the grain boundary is missing because of the difficulty of quantifying the atomic arrangement.

Any property of the grain boundary is dependent on the structure, which in turn is a function of the 5 DOF. The establishment of the relationship between the 5 DOF, the atomic structure, the physical mechanisms and the properties of a material dependent on the grain boundaries is fundamental for a comprehensive predictive modeling of materials’ behavior. The objective of the present project is to extend the concept of grain boundary engineering by using artificial intelligence (AI) and accelerate the determination of structure-property relationships. We aim to establish process-structure-mechanisms-properties (PSMP-)linkages of a material to better predict the behavior of a material but also to better understand the phenomena that operate during the synthesis, processing and operation of the materials by linking the physical mechanisms of the phenomena.

Within this context, the post-doctoral researcher will perform NEB molecular dynamics simulations of grain boundary migration and utilize concepts of materials informatics and machine learning such as persistent homology, principal component analysis to establish necessary PSP-linkages and to, finally, formulate reduced order constitutive models.

The project is funded by the Institut Carnot as a collaboration between Georgia Tech Europe (GTE) and the Laboratoire d’Étude des Microstructures et de Méchanique des Materiaux (LEM3) of the University of Lorraine.

The position will be for one year.

Contact persons

Applicants must submit their application consisting of CV and a letter of motivation addressing the topics of the project before April 20th, 2025, to: luis.barrales@me.gatech.edu

Requirements

The student must be in possession of a Ph.D. degree in Materials Science, Physics, Mechanical Engineering, Chemistry, or a related discipline at the moment of application.

Preferred Qualifications

• First-author peer reviewed publications
• Fluency of the English language
• Good command of the French language

Brief Description of Duties

• The researcher will conduct his research and ensure that it will be appropriately conducted following the policies and procedures of Georgia Tech Europe (GTE) and the University of Lorraine (LEM3).
• Coordinate the activities between the LEM3 and GTE.
• Perform all the activities necessary to fulfil the objectives of the research project.
• Analyze the results.
• Writing of scientific publications.
• Other duties as assigned, attending scientific conferences and meetings.

Specific Requirements

• Experience in molecular dynamics simulations particularly NEB.
• Experience in materials informatics (AI & ML applied to materials).